Vehicle control device and vehicle control system

ABSTRACT

Realized is a vehicle control device capable of performing automatic driving control that does not reduce turning accuracy of a host vehicle even when an object in a blind spot is different from an assumption and a vehicle speed decreases due to a rapid deceleration. A vehicle control device 10 includes a blind spot object estimation unit 24 that detects a blind spot region 320 of an external-field recognition sensor 12 that recognizes an external field and estimates a blind spot object 310 potential in the blind spot region 320, and a future trajectory generation unit 26 that generates a future trajectory of a host vehicle in consideration of a potential risk from the blind spot object 310 estimated by the blind spot object estimation unit 24 and surrounding information of a vehicle 1 that is the host vehicle. Furthermore, the vehicle control device 10 includes a target steering angle calculation unit 40 that calculates a curvature radius at which the vehicle 1 travels from the future trajectory generated by the future trajectory generation unit 26 and a past trajectory of the vehicle 1, and calculates a target steering angle of the vehicle 1 from the calculated curvature radius and an acceleration/deceleration of the vehicle 1.

TECHNICAL FIELD

The present invention relates to a vehicle control device and a vehiclecontrol system that control a vehicle such as an automobile.

BACKGROUND ART

A driving assistance device disclosed in PTL 1 is known as aconventional technique for realizing driving assistance consideringpotential risk of a pedestrian or the like hidden in a blind spot of anobstacle near a host vehicle.

For example, the abstract of PTL 1 discloses the driving assistancedevice “including calculation means for calculating, when an object thatcauses a blind spot exists in front of a host vehicle, a standard speedthat is a speed to be taken by the host vehicle in order to avoid acollision between a virtual moving object assumed to exist in the blindspot of the object and the host vehicle, estimation means for estimatinga risk degree related to a road on which the host vehicle is travelingbased on environment information indicating a traveling environmentrelated to the host vehicle, and correction means for correcting thecalculated standard speed based on the estimated risk degree”.

Further, the paragraph [0040] of the specification of PTL 1 disclosesthat “the risk degree estimation unit 12 further extracts one or aplurality of pieces of information (that is, near miss cases)corresponding to the estimated road environment and traffic environmentbased on tag information added to each of a plurality of pieces ofinformation included in a near miss database. The risk degree estimationunit 12 estimates the risk degree in comprehensive consideration of theestimated road environment and traffic environment and one or aplurality of pieces of extracted information”.

As described above, in a road environment where there is a blind spotsuch as a residential area, a method of realizing safer automaticdriving by predicting the type of a virtual moving object hidden in ablind spot based on near miss data and predicting the jumping out of thevirtual moving object has been developed.

CITATION LIST Patent Literature

PTL 1: JP 2019-069659 A

SUMMARY OF INVENTION Technical Problem

In the technique disclosed in PTL 1, the standard speed that is thespeed to be taken by the host vehicle in order to avoid the collisionbetween the virtual moving object assumed to exist in the blind spot ofan object and the host vehicle is calculated. Then, the risk degreerelated to the road on which the host vehicle is traveling is estimatedbased on the environment information indicating the travelingenvironment of the host vehicle, the standard speed calculated based onthe estimated risk degree is corrected, and the vehicle passes throughthe periphery of the blind spot at the corrected speed.

Therefore, when the estimated risk degree is wrong, for example, whenthe moving object that actually jumping out from the blind spot isdifferent from the estimation, rapid deceleration may be required tohandle the actual situation, and there is a probability that theautomatic steering control becomes unstable as a result of the rapiddeceleration.

An object of the present invention is to realize a vehicle controldevice and a vehicle control system capable of performing automaticdriving control that does not reduce turning accuracy of a host vehicleeven when an object in a blind spot is different from an estimation anda vehicle speed decreases due to rapid deceleration.

Solution to Problem

In order to achieve the above object, the present invention isconfigured as follows.

A vehicle control device includes a blind spot object estimation unitthat detects a blind spot region of an external-field recognition sensorthat recognizes an external field and estimates a blind spot objectpotential in the blind spot region, a future trajectory generation unitthat generates a future trajectory of a host vehicle in consideration ofa potential risk from the blind spot object estimated by the blind spotobject estimation unit and surrounding information of the host vehicle,and a target steering angle calculation unit that calculates a curvatureradius at which the host vehicle travels from the future trajectorygenerated by the future trajectory generation unit and a past trajectoryof the host vehicle, and calculates a target steering angle of the hostvehicle from the calculated curvature radius and anacceleration/deceleration of the host vehicle.

Further, a vehicle control system includes an external-field recognitionsensor that detects and recognizes an external field, an engine controldevice, a brake control device, a steering device, and a vehicle controldevice including a target acceleration/deceleration calculation unitthat outputs a target acceleration to the engine control device oroutputs a target deceleration to the brake control device, and a targetsteering angle calculation unit that calculates a target steering angleand outputs the target steering angle to the steering device. Thevehicle control device estimates a blind spot object in a blind spotregion that is undetectable by the external-field recognition sensor,calculates a curvature radius when a host vehicle turns at a rapidlydecelerated speed, and outputs a target steering angle calculated basedon the curvature radius to the steering device. The steering devicecontrols steering in accordance with the target steering angle.

Advantageous Effects of Invention

It is possible to realize a vehicle control device and a vehicle controlsystem capable of performing automatic driving control that does notreduce turning accuracy of a host vehicle even when an object in a blindspot is different from an estimation and a vehicle speed decreases dueto rapid deceleration.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a block diagram illustrating an aspect of a vehicle controlsystem of the present invention.

FIG. 2 is an explanatory diagram of blind spot object estimation.

FIG. 3 is a flowchart for explaining an operation until a futuretrajectory considering a potential risk is generated in the vehiclecontrol device.

FIG. 4A is a diagram illustrating a rotational translational changeamount of a vehicle from one calculation cycle to the current time.

FIG. 4B is an explanatory diagram of a sideslip angle of the vehicle.

FIG. 5A is a diagram illustrating coordinate points for the futuretrajectory of the vehicle and coordinate points for a past trajectory.

FIG. 5B is a diagram illustrating a result of adding information on acurvature radius R to each coordinate point.

FIG. 6 is an explanatory diagram of curve determination.

FIG. 7 is a flowchart for explaining an operation until a targetsteering angle is calculated from the future trajectory considering thepotential risk.

FIG. 8A is a diagram illustrating an acceleration/deceleration whenthere is the potential risk.

FIG. 8B is a diagram illustrating the acceleration/deceleration whenthere is no potential risk.

FIG. 9 is a diagram illustrating a case (solid line) of turning right atan intersection by using the curvature radius R and a case (broken line)of turning right at the intersection by using curve fitting.

DESCRIPTION OF EMBODIMENTS

Hereinafter, an embodiment of a vehicle control device and a vehiclecontrol system according to the present invention will be described withreference to the accompanying drawings.

Embodiment

FIG. 1 is a block diagram illustrating an aspect of a vehicle controlsystem of the present invention, and illustrates a vehicle controlsystem mounted on a vehicle 1 (host vehicle) and a vehicle controldevice 10 included in the vehicle control system. The vehicle controldevice 10 has a configuration illustrated within a broken line.

In FIG. 1 , the vehicle control device 10 is a system that calculates acurvature radius from a future trajectory (future traveling trajectory)considering a potential risk and a past trajectory (past travelingtrajectory), calculates a target steering angle for the futuretrajectory considering the potential risk, and then travels. The pasttrajectory may be generated from the future trajectory considering apotential risk, or may be a past trajectory acquired from a GNSS (globalnavigation satellite system).

It is assumed below that the past trajectory is generated from thefuture trajectory considering the potential risk.

The vehicle control system of the vehicle 1 on which the vehicle controldevice 10 is mounted includes a wheel speed sensor 11, an external-fieldrecognition sensor 12, a steering angle sensor 13, a steering device 14,a brake control device 15, and an engine control device 16.

The wheel speed sensor 11 is a wheel speed sensor that measures thewheel speed of the vehicle 1.

The external-field recognition sensor 12 is a sensor that detects andrecognizes an external field, and is a sensor that recognizes courseinformation such as a travel route and an obstacle of the vehicle 1 byusing a camera, a radar, a global navigation satellite system (GNSS) andmap information in combination.

The steering angle sensor 13 is a steering angle sensor that measures asteering angular velocity and a steering angle of the vehicle. Thesteering device 14 is a device as an aspect of a power steering devicecapable of electrically controlling a target steering angle.

The brake control device 15 is a device as an aspect of a mechanicalbrake device capable of electrically controlling a target deceleration.The engine control device 16 is a device as an aspect of an enginedevice capable of electrically controlling a target acceleration.

A map storage unit 20 stores road information and traffic lightinformation from a start point of automatic driving of the vehicle 1 toa target point, route information from the current position to thetarget point, a traffic rule database of a section where the vehicle 1travels, and the like.

A host vehicle position estimation unit 21 estimates a location(position) where the vehicle 1 (host vehicle) is present based onsurrounding information (surrounding environment information) obtainedby the external-field recognition sensor 12, a point cloud database (mapinformation) stored in the map storage unit 20, a vehicle speed of thevehicle 1 (host vehicle) obtained by the wheel speed sensor 11,information obtained by the global navigation satellite system (GNSS),and the like.

The map information processing unit 22 organizes lighting informationand the like of a traffic light on which the vehicle 1 is scheduled totravel based on lane center line information and traffic lightinformation of a road necessary for performing automatic driving basedon the map information stored in the map storage unit 20, converts thelighting information and the like into a format usable for automaticdriving of the vehicle 1 (host vehicle), and outputs the result of theconversion (generates and outputs travel use information).

The sensor information processing unit 23 receives an input of thesurrounding environment information obtained based on output information(external field information) of the external-field recognition sensor12, converts the surrounding environment information into objectinformation of a moving object existing around the vehicle 1, andoutputs the object information as surrounding information of the vehicle1 (host vehicle). Specific examples of the object information includeinformation indicating an attribute (type) of a moving object such as apedestrian, a bicycle, or a vehicle, and information indicating acurrent position and a current speed vector of the moving object. Notethat the moving object includes an object (for example, a stoppedvehicle, a parked vehicle, or the like) that is currently stopped butmay operate in the future.

The respective outputs of the host vehicle position estimation unit 21,the map information processing unit 22, and the sensor informationprocessing unit 23 are input to a moving object action prediction unit25. The moving object action prediction unit 25 predicts and calculatesa future position and a future speed of each moving object existingaround the vehicle 1 (host vehicle) based on the input information, andcalculates a risk for a host vehicle future trajectory. For example, theprediction and calculation of the speed may be calculated by linearprediction.

The moving object action prediction unit 25 does not estimate a movingobject such as a blind spot object 310 estimated by a blind spot objectestimation unit 24 described later.

The blind spot object estimation unit 24 will be described by using theexample illustrated in FIG. 2 . FIG. 2 is an explanatory diagram ofblind spot object estimation.

In FIG. 2 , various types of information necessary for estimating ablind spot object 310, which is a virtual moving object (pedestrian,bicycle, other vehicle, and the like) potential in a blind spot region320 of a nearby obstacle, are acquired. Specifically, road informationand map information are acquired from the map storage unit 20, andsurrounding information and the like from the sensor informationprocessing unit 23 are acquired.

Then, the blind spot object estimation unit 24 detects the blind spotregion 320 around the vehicle 1 based on various types of informationacquired from the map storage unit 20, the host vehicle positionestimation unit 21, the map information processing unit 22, the sensorinformation processing unit 23, and the moving object action predictionunit 25.

Here, as illustrated in FIG. 2 , the blind spot region 320 is a regionthat cannot be detected by the external-field recognition sensor 12 ofthe vehicle 1 due to obstacles such as other vehicles 300, fences, andsignboards under construction around the vehicle 1.

Note that, as described above, the blind spot object estimation unit 24acquires the various types of information from the map storage unit 20,the host vehicle position estimation unit 21, the map informationprocessing unit 22, the sensor information processing unit 23, and themoving object action prediction unit 25, but the input lines from therespective units such as the map storage unit 20 are omitted.

The blind spot object estimation unit 24 estimates the type and actionof the blind spot object 310 based on a feature amount (surroundinginformation, travel use information of the host vehicle) extracted fromthe surrounding information of the host vehicle from the sensorinformation processing unit 23 or the map information from the mapinformation processing unit 22.

A potential risk 330 is, for example, a region that is not manifested asa risk that the blind spot object 310 may possibly jump out from theblind spot region 320, but may become a risk in the future.

As a method of estimating the blind spot object 310, there is a methodof estimating the type of the blind spot object 310 based on the featureamount of a road situation extracted from the surrounding informationdetected by the sensor information processing unit 23 and the mapinformation by the map information processing unit 22. For example, itis possible to estimate whether the blind spot object 310 is a vehicle,a bicycle, or a pedestrian in consideration of various types ofinformation such as the presence or absence of a fence between a roadand a sidewalk, a surrounding park and time information, the presence orabsence of a school zone, the color of a signal (blinking red andyellow), a road sign, an accident occurrence point based on pastinformation, a parked vehicle or an emergency vehicle, or a normalvehicle, jumping out between oncoming vehicles when an oncoming lane iscongested, the presence or absence of a crosswalk, the entrance ofvarious stores, the vicinity of the entrance of a parking lot, and thelike.

Alternatively, it is also conceivable to statistically predict the typeof the blind spot object 310 based on information learned in advance byinputting point cloud information and image information obtained fromthe external-field recognition sensor 12 of the vehicle 1 to astatistical model such as a neural network. Furthermore, it is alsoconceivable to predict only an action tendency of the blind spot object310 instead of the type. A method of predicting a linear action tendencywhen the blind spot object 310 is predicted to be a child even when theshape of the blind spot object 310 is predicted to be in a stationarystate is also conceivable.

The information of the blind spot object 310 estimated in this manner isused as blind spot object estimation information at the time ofgenerating a future trajectory considering a potential risk to bedescribed later.

In FIG. 1 , the respective outputs of the host vehicle positionestimation unit 21, the map information processing unit 22, the sensorinformation processing unit 23, the moving object action prediction unit25, and the blind spot object estimation unit 24 are input to a futuretrajectory generation unit 26 considering the potential risk. The futuretrajectory generation unit 26 considering the potential risk generatesthe future trajectory of the vehicle 1 (host vehicle) in considerationof the potential risk from the blind spot object 310 estimated by theblind spot object estimation unit 24 and the surrounding information ofthe vehicle 1 (host vehicle).

The future trajectory generation unit 26 calculates the futuretrajectory considering the potential risk based on route information anda current vehicle state (speed, direction, position, and the like) sothat the vehicle 1 does not collide with a surrounding moving objectsuch as another vehicle.

Note that the future trajectory considering the potential risk means afuture trajectory on which the vehicle 1 does not collide with anothervehicle or a surrounding moving object and on which the vehicle 1 canstop or travel, or a future trajectory on which the vehicle 1 can travelor stop so as to minimize a blind spot of the external-field recognitionsensor 12 in order to minimize the potential risk as much as possiblebased on the route information and the current vehicle state (speed,direction, position, and the like).

FIG. 3 is a flowchart for explaining an operation until a futuretrajectory considering a potential risk is generated in the vehiclecontrol device 10. Each step in FIG. 3 will be described below.

(FIG. 3 : Step S301 (Map Information Acquisition))

A travel route, a road shape, traffic light information, a traffic ruledatabase, and the like are acquired from the external-field recognitionsensor 12 and stored in the map storage unit 20.

(FIG. 3 : Step S302 (Host Vehicle Position Acquisition)

The location where the vehicle 1 is present is estimated based oninformation obtained by a GNSS (global navigation satellite system) ofthe external-field recognition sensor 12 and the like.

(FIG. 3 : Steps S303 to S304 (Blind Spot Information Estimation, MovingObject Action Prediction)

A future position and a future speed of each moving object arecalculated by using outputs of the host vehicle position estimation unit21, the map information processing unit 22, and the sensor informationprocessing unit 23 as inputs. A potential risk is calculated inconsideration of a risk for a future trajectory and a risk based onblind spot information estimated by the blind spot informationestimation unit 24.

(FIG. 3 : Steps S305 (Whether or not there is Potential Risk), S306(Future Trajectory Considering Potential Risk), and S307 (Normal FutureTrajectory))

When there is a potential risk in Steps S303 to S304 (S305: YES), afuture trajectory considering a potential risk is generated (Step:S306). When there is no potential risk (S305: NO), a future trajectorybased on a lane center line may be generated, or a future trajectoryadapted to a steering operation of a driver may be generated (Step:S307).

A past trajectory generation unit 30 that generates the past travelingtrajectory of the vehicle 1 (host vehicle) may perform generation basedon the future trajectory considering the potential risk generated by thefuture trajectory generation unit 26, or may perform generation based onposition information acquired from the global navigation satellitesystem (GNSS).

As an example, generation of a past trajectory from the futuretrajectory considering the potential risk will be described.

In the past trajectory generation, a vehicle speed V (m/s) detected bythe wheel speed sensor 11, a front wheel steering angle δ (rad) detectedby the steering angle sensor 13, a stability factor A of the vehicle 1,and a wheelbase l (m) of the vehicle 1 are acquired to calculate the yawrate γ (rad/s), and calculate the rotational translational change amountof the vehicle 1. The yaw rate γ can be represented by the followingExpression (1).

$\begin{matrix}\lbrack {{Math}.1} \rbrack &  \\{\gamma = {\frac{1}{1 + {AV^{2}}}\frac{V}{l}\delta}} & (1)\end{matrix}$

Note that, instead of acquiring the front wheel steering angle δ,calculation can be performed by using the detection value of a yaw ratesensor.

FIG. 4A is a diagram illustrating a rotational translational changeamount of the vehicle 1 per calculation cycle TS (s), that is, from atime before one calculation cycle to the current time. In addition, FIG.4B is an explanatory diagram of a sideslip angle of the vehicle 1.

When the rotational change amount of the vehicle 1 is set as Δθ (rad),the translational change amount of the vehicle 1 in a vehicle lengthdirection is set as Δx (m), the translational change amount of thevehicle 1 in a vehicle width direction is set as Δy (m) as illustratedin FIG. 4A, and the sideslip angle of the vehicle 1 is set as β asillustrated in FIG. 4B, Δθ, β, Δx, and Δy can be represented by thefollowing expressions (2) to (4).

[Math. 2]

Δθ=γ×Ts  (2)

[Math. 3]

Δx=V×Ts×cos(Δθ−β)  (3)

[Math. 4]

Δy=V×Ts×sin(Δθ−β)  (4)

The sideslip β illustrated in FIG. 4B is calculated by acquiring theweight m (kg) of the vehicle 1, the distance lf (m) from the center ofgravity of the vehicle 1 to the front wheels, the distance lr (m) fromthe center of gravity of the vehicle 1 to the rear wheels, the wheelbasel (m) of the vehicle 1, the vehicle speed V (m/s) detected from thewheel speed sensor 11, the stability factor A of the vehicle 1, thefront wheel steering angle δ (rad) of the vehicle 1, and the corneringpower Kr of the vehicle 1.

The sideslip β can be represented by the following mathematicalexpression (5).

$\begin{matrix}\lbrack {{Math}.5} \rbrack &  \\{\beta = {\frac{1 - {\frac{ml_{f}}{2{ll}_{r}K_{r}}V^{2}}}{1 + {AV^{2}}}\frac{l_{r}}{l}\delta}} & (5)\end{matrix}$

The affine transformation is performed on the future trajectoryconsidering the potential risk by using the change amounts Δθ, Δx, andΔy of the vehicle 1, and the result of the affine transformation isstored as the past trajectory for each calculation cycle.

A curvature radius calculation unit 31 that calculates the curvatureradius of the curve on which the vehicle 1 (host vehicle) travels willbe described with reference to FIG. 5A. FIG. 5A is a diagramillustrating coordinate points for the future trajectory of the vehicle1 and coordinate points for a past trajectory. In FIG. 5A, a circlepassing through a coordinate point on the future trajectory consideringthe potential risk at the future time Ts (s), a coordinate point of thepast trajectory, and any point in consideration of the potential risk atthe is calculated, and a radius of the circle is set as a curvatureradius R.

FIG. 5A is a diagram in which the curvature radius R is calculated fromeach coordinate point. Assuming that the center coordinates of thecircle are (cx, cy), the curvature radius R can be represented by thefollowing expressions (6) to (8).

[Math. 6]

(x1−cx)²+(y1−cy)² =R ²  (6)

[Math. 7]

(x2−cx)²+(y2−cy)² =R ²  (7)

[Math. 8]

(x3−cx)²+(y ³ −cy)² =R ²  (8)

As the three points for calculating the curvature radius R, coordinatepoints separated from any one point by the same distance are used. Thedistance is, for example, the sum of d1, d2, and d3 in FIG. 5A. As aresult of calculating the distance, when the distance is between thecoordinate point and the coordinate point, the curvature radius iscalculated by an inner split point or linear interpolation between thecoordinate points.

The calculated curvature radius R is added to information of eachcoordinate point of the future trajectory and is expressed byinformation of (x1, y1, R1), . . . , and (xN, yN, RN). FIG. 5Billustrates a result of adding information on the curvature radius R toeach coordinate point.

Next, the curve determination unit 32 will be described with referenceto FIG. 6 . FIG. 6 is an explanatory diagram of curve determination. InFIG. 6 , the vertical axis indicates the curvature radius (m), and thehorizontal axis indicates the traveling time. The curve determinationunit 32 determines whether the vehicle 1, which is the host vehicle,travels in a curve.

When the vehicle 1 turns right at an intersection as illustrated in FIG.2 , the curvature radius R before entering the intersection has a smallchange amount (inclination a). Thus, it can be determined that thevehicle 1 is traveling on a straight line.

Then, when the vehicle 1 enters the intersection, the curvature radius Ris calculated to gradually decrease. The change amount (inclination a)of the curvature radius R stored at each coordinate point of the futuretrajectory and the past trajectory can be calculated and it can bedetermined that the vehicle 1 has entered the intersection. Thiscorresponds to a case during turning illustrated in FIG. 6 .

Then, when the vehicle 1 exits the intersection, the curvature radius Ris calculated to gradually increase. The change amount (inclination a)of the curvature radius R stored at each coordinate point of the futuretrajectory and the past trajectory is calculated, and it can bedetermined that the vehicle 1 has left the intersection. The changeamount (inclination a) of the curvature radius R can be represented bythe following expression (9).

$\begin{matrix}\lbrack {{Math}.9} \rbrack &  \\{a = \frac{\begin{matrix}{\sum_{n = 1}^{n}( {{x_{1}( {{inter} - {{coordinate}{distance}}} )} -} } \\{\overset{\_}{x}( {{inter} - {{coordinate}{distance}{average}}} )} \\( {{y_{i}( {{curvature}{radius}} )} -}  \\ {\overset{\_}{y}( {{curvature}{radius}{average}} )} )\end{matrix}}{\begin{matrix}{\sum_{n = 1}^{n}( {{x_{1}( {{inter} - {{coordinate}{distance}}} )} -} } \\{\overset{\_}{x}( {{inter} - {{coordinate}{distance}{average}}} )}^{2}\end{matrix}}} & (9)\end{matrix}$

A speed calculation unit 33 calculates the actual vehicle speed of thevehicle 1 (calculates the speed of the host vehicle) based on wheelspeed information acquired from the wheel speed sensor 11.

A target steering angle calculation unit 40 calculates a target steeringangle of the vehicle 1 based on the curvature radius calculated andoutput by the curvature radius calculation unit 31 and input informationof an output of the determination result of the curve determination unit32. First, the target steering angle calculation unit 40 determines thevalue of the curvature radius R at each coordinate point from the inputof the curve determination unit 32. For example, the curvature radius Ron the past trajectory of the vehicle 1 is used at the time of enteringthe curve, and the curvature radius R on the future trajectory of thevehicle 1 is used at the time of exiting the curve.

The target steering angle is calculated by acquiring the curvatureradius R, the vehicle speed V obtained by the wheel speed sensor 11, thewheelbase l of the vehicle 1, the stability factor A of the vehicle 1,the gear_ratio of the vehicle 1, and the front wheel steering angle δ.The target steering angle can be represented by the followingexpressions (10) and (11).

$\begin{matrix}\lbrack {{Math}.10} \rbrack &  \\{\delta = {( {1\  + {AV^{2}}} )\frac{l}{R}}} & (10)\end{matrix}$ $\begin{matrix}\lbrack {{Math}.11} \rbrack &  \\{{{Target}{steering}{angle}} = {\delta \times {gear\_ ratio}}} & (11)\end{matrix}$

The target steering angle calculation unit 40 outputs the calculatedtarget steering angle to the steering device 14. The steering device 14drives the steering to reach the target steering angle output by thetarget steering angle calculation unit 40.

A target acceleration/deceleration calculation unit 41 corrects thespeed of the vehicle 1 calculated by the speed calculation unit 33 basedon the future trajectory considering the potential risk, which has beengenerated by the future trajectory generation unit 26 considering thepotential risk, and calculates the target acceleration/deceleration.This speed correction is performed because, when the vehicle 1 continuestraveling at the current speed, and a moving object having a speedhigher than that of the blind spot object 310 estimated from the blindspot region 320 jumps out (for example, when the blind spot object 310is estimated to be a pedestrian but is actually a bicycle), it isnecessary to avoid a collision by a rapid deceleration.

However, in this case, the ride comfort of the vehicle 1 issignificantly deteriorated. Thus, when the vehicle 1 passes near theblind spot region 320, the vehicle 1 is decelerated in advance to atarget blind spot passing speed lower than the current speed. Bydecelerating the vehicle 1 in advance, even when a moving object havinga speed higher than that of the estimated blind spot object 310 jumpsout, it is possible to alleviate the degree of a rapid deceleration andsuppress deterioration of ride comfort.

The target acceleration/deceleration calculated by the targetacceleration/deceleration calculation unit 41 is a target accelerationand a target deceleration, and the target acceleration is output to theengine control device 16. The engine control device 16 controls theengine so that the vehicle 1 (host vehicle) has the target accelerationcalculated by the target acceleration/deceleration calculation unit 41.

Further, the target deceleration calculated by the targetacceleration/deceleration calculation unit 41 is output to the brakecontrol device 15. The brake control device 15 controls the brake sothat the vehicle 1 (host vehicle) has the target deceleration calculatedby the target acceleration/deceleration calculation unit 41.

The target acceleration/deceleration calculation unit 41 outputs thetarget acceleration to the engine control device 16 or outputs thetarget deceleration to the brake control device 15.

FIG. 7 is a flowchart for explaining an operation until a targetsteering angle is calculated from the future trajectory considering thepotential risk in the vehicle control device 10. Each step in FIG. 7will be described below.

(FIG. 7 : Steps S601 to S603)

In Steps 601 and 602, the past trajectory is generated from the futuretrajectory considering the potential risk, which has been generated fromthe respective outputs of the host vehicle position estimation unit 21,the map information processing unit 22, the sensor informationprocessing unit 23, the moving object action prediction unit 25, and theblind spot object estimation unit 24. Then, in Step S603, the curvatureradius is calculated from the past trajectory and the future trajectory.The future trajectory considering the potential risk includes atrajectory considering ride comfort such as an acceleration by an engineand a deceleration by a brake.

FIG. 8A is a diagram illustrating an acceleration/deceleration whenthere is a potential risk, and FIG. 8B is a diagram illustrating anacceleration/deceleration when there is no potential risk.

When there is a potential risk while turning right or left at anintersection, a T-junction, or the like, acceleration/deceleration isperformed in the middle of turning. When the acceleration/decelerationis performed, it is conceivable that the distance between trajectorytrack point arrays of the future trajectory considering the potentialrisk changes back and forth.

In the related art, when the future trajectory is generated from thelane center line, curve fitting or linear fitting using an approximateexpression is used. In a case of a curve of about R 100, an actualfuture trajectory and an approximate trajectory are almost the same.However, in a case of a curve of about R 10 such as a right or left turnat an intersection, an error of the approximate future trajectoryincreases.

Furthermore, in the case of trajectory following control using curvefitting or linear fitting using the approximate expression, the resultof the approximate expression changes each time the distance between thetrack point arrays increases or decreases, and there is a concern aboutdeterioration of ride comfort. On the other hand, when the curvatureradius is used, the influence is small even when the distance betweenthe trajectory point arrays changes. Thus, it is possible to perform theautomatic driving control so as not to deteriorate the ride comfort.

Although an example in which the past trajectory is generated from thefuture trajectory has been described, the past trajectory may begenerated from the GNSS (global navigation satellite system). Thecurvature radius R information is added to each trajectory point byusing the generated past trajectory and the future trajectoryconsidering the potential risk.

(FIG. 7 : Steps S604 to S605)

If the change amount (inclination) in the curvature radius R of thefuture trajectory considering the potential risk tends to decrease(step: S604 YES), it can be determined that the vehicle is approachingthe entrance of the curve. If the change amount (inclination) in thecurvature radius R of the future trajectory considering the potentialrisk tends to increase (step: S605 YES), it can be determined that thevehicle is approaching the exit of the curve. When it is not a curveentrance or a curve exit, control is performed as a straight line.

(FIG. 7 : Steps S606 to S609)

When it is determined as a straight line in Step S606, in curvatureradius setting (Step S609) for the target steering angle, the curvatureradius R is defined to be equal to or greater than R 1000. When thecurve entrance is determined in Step S608, in the curvature radiussetting (Step S609) for the target steering angle, the curvature radiusR of the past trajectory is used from the center of gravity of thevehicle 1. Although it is assumed from the center of gravity of thevehicle 1, the center of the vehicle 1, the center of the front wheelaxle, or the center of the rear wheel axle of the vehicle 1 may be used.

When the curve exit is determined in Step S607, in the curvature radiussetting (Step S609) for the target steering angle, the curvature radiusR of the future trajectory considering the potential risk is used fromthe center of gravity of the vehicle 1. Although it is assumed from thecenter of gravity of the vehicle 1, the center of the vehicle 1, thecenter of the front wheel axle, or the center of the rear wheel axle ofthe vehicle 1 may be used.

(FIG. 7 : Step S610)

The target acceleration/deceleration is calculated from the futuretrajectory considering the potential risk and the current speed of thevehicle 1. For the target acceleration/deceleration, the blind spotobject 310 jumping out of the blind spot region 320 is estimated, andspeed control is performed in advance so as not to cause rapiddeceleration.

(FIG. 7 : Step S611)

The target steering angle is calculated by using the curvature radius Rset in Step S609 and the target acceleration/deceleration calculated inStep S610. When the target steering angle is calculated with thecurvature radius R, it is necessary to calculate the rotation directionof the vehicle 1. As a method of obtaining the rotation direction, forexample, the rotation direction may be calculated from the coordinatepoints of the future trajectory considering the potential risk, or therotation direction may be calculated by using an outer product ofvectors.

In the embodiment, the curvature radius and the target steering angle(target steering amount) are set such that the lateral acceleration ofthe vehicle 1 (host vehicle) is smaller than 0.2 G.

FIG. 9 is a diagram illustrating a case (solid line) of turning right atan intersection by using the curvature radius R and a case (broken line)of turning right at the intersection by using curve fitting. Since thecalculation of the target steering angle by curve fitting is anapproximate expression, it is conceivable to travel on the inner side ofthe future trajectory considering the potential risk, and traveling onthe inner side causes the lateral G of the vehicle 1 to be stronglyapplied, and there is a concern that the ride comfort is deteriorated.

The vehicle control device 10 using the curvature radius R does nottravel on the inner side of the future trajectory considering thepotential risk, and can smoothly connect the curvature radius R by usingthe curve determination unit 32.

As described above, the vehicle control device 10 can perform automaticdriving control without deteriorating the turning performance of thehost vehicle even when acceleration/deceleration occurs on the futuretrajectory considering the potential risk.

As described above, according to the embodiment of the presentinvention, the vehicle control device 10 includes the blind spot objectestimation unit 24 that detects the blind spot region 320 of theexternal-field recognition sensor 12 that recognizes an external fieldand estimates the blind spot object 310 potential in the blind spotregion 320, the future trajectory generation unit 26 that generates afuture trajectory of the vehicle 1 in consideration of the potentialrisk from the blind spot object 310 estimated by the blind spot objectestimation unit 24 and surrounding information of the vehicle 1 beingthe host vehicle, and the target steering angle calculation unit 40 thatcalculates the curvature radius at which the vehicle 1 travels from thefuture trajectory generated by the future trajectory generation unit 26and the past trajectory of the vehicle 1, and calculates the targetsteering angle of the vehicle 1 from the calculated curvature radius andan acceleration/deceleration of the vehicle 1. Then, the blind spotobject in the blind spot region that is undetectable by theexternal-field recognition sensor 12 is estimated, the curvature radiusand the speed of the vehicle 1 when the vehicle 1 turns at a rapidlydecelerated speed are calculated, and the calculated curvature radiusand the target steering angle are output to the steering device 14. Thesteering device 14 is configured to control the steering in accordancewith the target steering angle.

Therefore, it is possible to realize a vehicle control device and avehicle control system capable of performing automatic driving controlthat does not reduce turning accuracy of a host vehicle even when anobject in a blind spot is different from an estimation and a vehiclespeed decreases due to rapid deceleration.

The present invention is not limited to the above embodiment, andvarious modification examples may be provided. For example, the aboveembodiment is described in detail in order to explain the presentinvention in an easy-to-understand manner, and the above embodiment isnot necessarily limited to a case including all the describedconfigurations.

Some or all of the configurations, functions, processing units,processing means, and the like may be realized in hardware by beingdesigned with an integrated circuit, for example.

Further, the above-described respective components, functions, and thelike may be realized by software by the processor interpreting andexecuting a program for realizing the respective functions. Informationsuch as a program, a table, and a file, that realizes each function canbe stored in a memory, a recording medium such as a hard disk and asolid state drive (SSD), or a recording medium such as an IC card, an SDcard, and a DVD.

REFERENCE SIGNS LIST

-   1 host vehicle-   10 vehicle control device-   11 wheel speed sensor-   12 external-field recognition sensor-   13 steering angle sensor-   14 steering device-   15 brake control device-   16 engine control device-   20 map storage unit-   21 host vehicle position estimation unit-   22 map information processing unit-   23 sensor information processing unit-   24 blind spot object estimation unit-   25 moving object action prediction unit-   26 future trajectory generation unit considering potential risk-   30 past trajectory generation unit-   31 curvature radius calculation unit-   32 curve determination unit-   40 target steering angle calculation unit-   41 target acceleration/deceleration calculation unit-   300 other vehicle-   310 blind spot object-   320 blind spot region-   330 potential risk

1. A vehicle control device comprising: a blind spot object estimationunit that detects a blind spot region of an external-field recognitionsensor that recognizes an external field and estimates a blind spotobject potential in the blind spot region; a future trajectorygeneration unit that generates a future trajectory of a host vehicle inconsideration of a potential risk from the blind spot object estimatedby the blind spot object estimation unit and surrounding information ofthe host vehicle; and a target steering angle calculation unit thatcalculates a curvature radius at which the host vehicle travels from thefuture trajectory generated by the future trajectory generation unit anda past trajectory of the host vehicle, and calculates a target steeringangle of the host vehicle from the calculated curvature radius and anacceleration/deceleration of the host vehicle.
 2. The vehicle controldevice according to claim 1, wherein the blind spot object estimationunit estimates a type and an action of the blind spot object based on afeature amount extracted from the surrounding information of the hostvehicle or map information.
 3. The vehicle control device according toclaim 2, further comprising: a sensor information processing unit thatreceives an input of surrounding environment information obtained basedon external field information from a sensor that recognizes the externalfield, converts the surrounding environment information into objectinformation of a moving object existing around the host vehicle, andoutputs the object information as the surrounding information of thehost vehicle; and a map information processing unit that generates andoutputs travel use information that is usable for automatic driving ofthe host vehicle from the map information, wherein the blind spot objectestimation unit estimates the type and the action of the blind spotobject based on the feature amount extracted from the surroundinginformation of the host vehicle or the map information.
 4. The vehiclecontrol device according to claim 3, further comprising: a host vehicleposition estimation unit that estimates a position of the host vehicle;and a moving object action prediction unit that predicts an action of amoving object existing around the host vehicle based on the surroundinginformation output from the sensor information processing unit, thetravel use information output from the map information processing unit,and the position of the host vehicle estimated by the host vehicleposition estimation unit, wherein the future trajectory generation unitgenerates the future trajectory of the host vehicle based on the traveluse information output from the map information processing unit, theposition of the host vehicle estimated by the host vehicle positionestimation unit, the type and action of the blind spot object estimatedby the blind spot object estimation unit, and the action of the movingobject predicted by the moving object action prediction unit.
 5. Thevehicle control device according to claim 4, further comprising: a speedcalculation unit that calculates a speed of the host vehicle; and atarget acceleration/deceleration calculation unit that corrects thespeed of the host vehicle calculated by the speed calculation unit,based on the future trajectory generated by the future trajectorygeneration unit, and calculates a target acceleration/deceleration. 6.The vehicle control device according to claim 5, further comprising: acurve determination unit that determines whether or not the host vehicletravels in a curve and outputs a determination result; and a curvatureradius calculation unit that calculates the curvature radius of a curveon which the host vehicle travels, wherein the target steering anglecalculation unit calculates the target steering angle of the hostvehicle based on the curvature radius calculated by the curvature radiuscalculation unit and the determination result of the curve determinationunit.
 7. The vehicle control device according to claim 6, wherein thetarget steering angle calculation unit sets the curvature radius and thetarget steering angle such that a lateral acceleration of the hostvehicle is smaller than 0.2 G.
 8. A vehicle control system comprising:an external-field recognition sensor that detects and recognizes anexternal field; an engine control device; a brake control device; asteering device; and a vehicle control device including a targetacceleration/deceleration calculation unit that outputs a targetacceleration to the engine control device or outputs a targetdeceleration to the brake control device, and a target steering anglecalculation unit that calculates a target steering angle and outputs thetarget steering angle to the steering device, wherein the vehiclecontrol device estimates a blind spot object in a blind spot region thatis undetectable by the external-field recognition sensor, calculates acurvature radius when a host vehicle turns at a rapidly deceleratedspeed, and outputs a target steering angle calculated based on thecurvature radius to the steering device, and the steering devicecontrols steering in accordance with the target steering angle.
 9. Thevehicle control system according to claim 8, wherein the vehicle controldevice further includes a blind spot object estimation unit that detectsa blind spot region of a sensor that recognizes an external field andestimates a blind spot object potential in the blind spot region, afuture trajectory generation unit that generates a future trajectory ofthe host vehicle in consideration of a potential risk from the blindspot object estimated by the blind spot object estimation unit andsurrounding information of the host vehicle, and the target steeringangle calculation unit calculates the curvature radius at which the hostvehicle travels from the future trajectory generated by the futuretrajectory generation unit and a past trajectory of the host vehicle,and calculates the target steering angle of the host vehicle from thecalculated curvature radius and an acceleration/deceleration of the hostvehicle.